Zi-Yu Wang
Papers
1
Total Citations
3
H-Index
1
About
Zi-Yu Wang is a robotics researcher whose work bridges autonomous navigation and human-robot interaction, with a focus on accessible, real-world applications. Wang’s most cited study, “Integration of open source platform Duckietown and gesture recognition as an interactive interface for the museum robotic guide” (2018, 3 citations), addresses the pressing challenge of labor shortages due to population aging by designing an automatic museum robotic guide. This work integrates Duckietown—an open-source platform for self-driving cars—with gesture recognition, enabling intuitive, hands-free interaction for visitors. By combining low-cost, scalable robotics with natural user interfaces, Wang demonstrates a practical pathway for deploying autonomous guides in public spaces like museums, exhibitions, and libraries. While still early in their career, Wang’s contribution highlights a commitment to socially impactful robotics—making technology more accessible to aging populations and non-expert users. Their research sits at the intersection of autonomous systems, computer vision, and human-centered design, offering a blueprint for how open-source platforms can be repurposed for assistive, interactive roles in everyday environments.
Research Focus
Key Achievements
Top Papers
- 1